Evaluating the Effectiveness of GARCH models in the Estimation of Conditional Value at Risk in listed companies of the Tehran Stock Exchange: Accounting Data Approach
سال انتشار: 1402
نوع سند: مقاله ژورنالی
زبان: انگلیسی
مشاهده: 203
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شناسه ملی سند علمی:
JR_IJFMA-8-29_018
تاریخ نمایه سازی: 18 دی 1401
چکیده مقاله:
Predictions are extremely important for a better decision-making. Uncertainty in decision making makes investors always seek to assess and estimate risk to minimize potential losses. Conditional risk value (CvaR) is considered as a comprehensive measure of risk that has been considered a useful tool in recent years. Due to the characteristics of capital market data, not all models will be able to make accurate predictions, and among the multitude of models, only the models which make predictions can correctly explain this market.In this study, according to the existing theoretical foundations and using Delphi model and analysis and review of experts, first the accounting variables in the financial statements are effective in predicting the conditional risk value, then the data of accepted companies are used. In Tehran Stock Exchange during ۲۰۱۲-۲۰۱۸, we evaluated the capability of GARCH and Markov index models in predicting conditional risk value as a criterion for predicting coherent risk. The results showed that the estimates made with the GARCH model (۱, ۱) are closer to reality with the distribution of T-Student.
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نویسندگان
Hossein Aryaeinezhad
PhD Student, Department of Accounting, Islamic Azad University, Aliabad Katoul Branch, Aliabad Katoul, Iran
Arash Naderian
Assistant professor, Department of Accounting, Aliabad Katoul branch, Islamic Azad University, Aliabad Katoul, Iran
Hosein Didehkhani
Assistant Professor, Department of Financial Engineering , Aliabad Katoul Branch, Islamic Azad University, Aliabad katul , Iran
Ali Khozein
Assistant Professor of Accounting, Aliabad Katoul Branch, Islamic Azad University, Aliabad Katoul, Iran
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